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Can We Predict Individual Combined Benefit and Harm of Therapy? Warfarin Therapy for Atrial Fibrillation as a Test Case

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  • Guowei Li
  • Lehana Thabane
  • Thomas Delate
  • Daniel M Witt
  • Mitchell A H Levine
  • Ji Cheng
  • Anne Holbrook

Abstract

Objectives: To construct and validate a prediction model for individual combined benefit and harm outcomes (stroke with no major bleeding, major bleeding with no stroke, neither event, or both) in patients with atrial fibrillation (AF) with and without warfarin therapy. Methods: Using the Kaiser Permanente Colorado databases, we included patients newly diagnosed with AF between January 1, 2005 and December 31, 2012 for model construction and validation. The primary outcome was a prediction model of composite of stroke or major bleeding using polytomous logistic regression (PLR) modelling. The secondary outcome was a prediction model of all-cause mortality using the Cox regression modelling. Results: We included 9074 patients with 4537 and 4537 warfarin users and non-users, respectively. In the derivation cohort (n = 4632), there were 136 strokes (2.94%), 280 major bleedings (6.04%) and 1194 deaths (25.78%) occurred. In the prediction models, warfarin use was not significantly associated with risk of stroke, but increased the risk of major bleeding and decreased the risk of death. Both the PLR and Cox models were robust, internally and externally validated, and with acceptable model performances. Conclusions: In this study, we introduce a new methodology for predicting individual combined benefit and harm outcomes associated with warfarin therapy for patients with AF. Should this approach be validated in other patient populations, it has potential advantages over existing risk stratification approaches as a patient-physician aid for shared decision-making

Suggested Citation

  • Guowei Li & Lehana Thabane & Thomas Delate & Daniel M Witt & Mitchell A H Levine & Ji Cheng & Anne Holbrook, 2016. "Can We Predict Individual Combined Benefit and Harm of Therapy? Warfarin Therapy for Atrial Fibrillation as a Test Case," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-16, August.
  • Handle: RePEc:plo:pone00:0160713
    DOI: 10.1371/journal.pone.0160713
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    References listed on IDEAS

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    1. Wen-Hsien Ho & King-Teh Lee & Hong-Yaw Chen & Te-Wei Ho & Herng-Chia Chiu, 2012. "Disease-Free Survival after Hepatic Resection in Hepatocellular Carcinoma Patients: A Prediction Approach Using Artificial Neural Network," PLOS ONE, Public Library of Science, vol. 7(1), pages 1-9, January.
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